8 citations · 31 across the 13 of their papers we have counts for
Showing 2018 · stat.MLShow all
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stat.ML2018
Double Adaptive Stochastic Gradient Optimization
Kin Gutierrez, Jin Li, Cristian Challu +1
Adaptive moment methods have been remarkably successful in deep learning optimization, particularly in the presence of noisy and/or sparse gradients. We further the advantages of a…
stat.ML2018
On the Interaction Effects Between Prediction and Clustering
Matt Barnes, Artur Dubrawski
Machine learning systems increasingly depend on pipelines of multiple algorithms to provide high quality and well structured predictions. This paper argues interaction effects betw…
stat.ML2018
Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information
Yichong Xu, Sivaraman Balakrishnan, Aarti Singh +1
In supervised learning, we typically leverage a fully labeled dataset to design methods for function estimation or prediction. In many practical situations, we are able to obtain a…